ArticleGenetics2006
Quantitative trait linkage analysis using Gaussian copulas.
Article in Genetics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- A novel phenotype imputation method with copula model.BMC bioinformatics · 2024Article
- Copula miss-specification in REML multivariate genetic animal model estimation.Genetics, selection, evolution : GSE · 2022Article
- A distance-type measure approach to the analysis of copy number variation in DNA sequencing data.BMC genomics · 2019Article
- Directional dependence between major cities in China based on copula regression on air pollution measurements.PloS one · 2019Article
- Copula directional dependence for inference and statistical analysis of whole-brain connectivity from fMRI data.Brain and behavior · 2019Article
- A copula model for joint modeling of longitudinal and time-invariant mixed outcomes.Statistics in medicine · 2018Article
- Time-varying copula models for longitudinal data.Statistics and its interface · 2018Article
- Copula regression analysis of simultaneously recorded frontal eye field and inferotemporal spiking activity during object-based working memory.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2015Article
- A Gaussian copula approach for the analysis of secondary phenotypes in case-control genetic association studies.Biostatistics (Oxford, England) · 2012Article
- Evaluation of a bayesian model integration-based method for censored data.Human heredity · 2012Article
- A powerful test of parent-of-origin effects for quantitative traits using haplotypes.PloS one · 2011Article
- Article
- Rank-based inverse normal transformations are increasingly used, but are they merited?Behavior genetics · 2009Article
- Efficient calculation of empirical P-values for genome-wide linkage analysis through weighted permutation.Behavior genetics · 2009Article
- A copula method for modeling directional dependence of genes.BMC bioinformatics · 2008Article
- Heritability of cardiovascular and personality traits in 6,148 Sardinians.PLoS genetics · 2006Article
- Modeling Multiple Responses via Bootstrapping Margins with an Application to Genetic Association Testing.Statistics and its interfaceArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Mapping and identifying variants that influence quantitative traits is an important problem for genetic studies. Traditional QTL mapping relies on a variance-components (VC) approach with the key assumption that the trait values in a family follow a multivariate normal distribution. Violation of this assumption can lead to inflated type I error, reduced power, and biased parameter estimates. To accommodate nonnormally distributed data, we developed and implemented a modified VC method, which we call the "copula VC method," that directly models the nonnormal distribution using Gaussian copulas. The copula VC method allows the analysis of continuous, discrete, and censored trait data, and the standard VC method is a special case when the data are distributed as multivariate normal. Through the use of link functions, the copula VC method can easily incorporate covariates. We use computer simulations to show that the proposed method yields unbiased parameter estimates, correct type I error rates, and improved power for testing linkage with a variety of nonnormal traits as compared with the standard VC and the regression-based methods.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.